[HN Gopher] Launch HN: Baseplate (YC W23) - Back end-as-a-servic...
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Launch HN: Baseplate (YC W23) - Back end-as-a-service for LLM apps
Hey HN! Andrew and Ani here, co founders of Baseplate
(https://www.baseplate.ai). We're building a unified backend for
LLM apps, where you can manage your data, prompts, embeddings, and
deployments. Demo video here:
https://www.loom.com/share/97bc388f6b6c4c95bf6c51c832bfd8a5. Most
LLM apps can be built by properly integrating LLMs with a knowledge
base consisting of domain-specific or company-specific data. The
scope of this knowledge base can change based on the task- it can
be something as narrow and static as your API docs or as broad and
fluid as meeting transcripts from your customer support calls. To
effectively use their data, most teams need to build a similar
stack--datasource integrations, async embedding jobs, vector
databases, bucket storage for non textual data, a way to version
prompts, and potentially an additional database for the text data.
Baseplate provides much of the backend for you through simple APIs,
so you can focus on building your core product and less on building
common infra. At my previous role at Google X, I worked on
building data infrastructure for geospatial data pipelines and
knowledge graphs. One of my projects was to integrate knowledge
graph triples with LaMDA, and I discovered the need for LLM tooling
after using one of Google's initial prompt chaining tools. Ani was
a PM at Logitech, shipping products in their Computer Vision team,
and at the same time building side projects with GPT-3. The core
of Baseplate is our simplified multimodal database, which allows
you to store text, embeddings, data, and metadata in one place.
Through a spreadsheet-style interface, you can edit your vectors
and metadata (which is surprisingly complex with existing tools),
and add images that can be returned at query time. Users can choose
between standard semantic search or hybrid search (weighted
keywords/semantics for larger, more technical datasets). Hybrid
search on Baseplate utilizes two open-source models that can be
tuned for your use case (instructor & SPLADE). Datasets are
organized into documents, which you can keep in sync through our
API or through the UI (this way you can keep your datasets fresh
when ingesting data from Google Drive/Notion/ etc). After your
datasets are set up, we have an App Builder where you can iterate
on prompts with input variables, and create context variables that
pull directly from a dataset at query time. We give you all the
knobs and dials, so that you can configure exactly how your search
is performed and how it is integrated with your prompt. When
you're satisfied with an app configuration, you deploy it to an
endpoint. All you need is a single API call and we'll pull from one
(or multiple) datasets in your app and inject the text into the
prompt. We also return all the search results in the API response,
so you can build a custom UX around images or links in your
dataset. Endpoints have built in utilities for human feedback and
logging. With GPT-4 being able to take images as input, we will
soon be working on a way to pipe images from your dataset directly
to the model. And all of these tools are in a team workspace, where
you can quickly iterate and build together. We just started
offering self-serve sign up, and our pricing is currently $35/month
per user for our Pro plan and $500/team on our Team plan. Feel free
to sign up and poke around. We'd love to hear feedback from the
community, and look forward to your comments!
Author : andrewlu0
Score : 72 points
Date : 2023-03-30 16:56 UTC (6 hours ago)
| vpendse wrote:
| [flagged]
| cetaceaa wrote:
| Congrats Andrew and Ani! Big fan of the App Builder
| functionality, and excited for GPT-4 integration.
|
| Do you have any ideas/plans for providing pre-loaded off-the-
| shelf app configurations, perhaps specialized to a particular
| task or industry that can then be further tweaked? Or are you
| committed to a "BYOB" approach?
|
| Anyway, congrats again. Really impressed with what's coming out
| of this YC class so far.
| andrewlu0 wrote:
| Thats actually a pretty good idea, we'll consider it! One thing
| is since our hybrid datasets are based off instructor-large
| embeddings, we'll later offer the ability to set the embedding
| "instruction", which can be tweaked for data from different
| domains. It might play nicely with an app template for a
| specific task/industry
| instagary wrote:
| So does this ultimately allow me do this workflow?
|
| 1. Say I have a blog post 2. I run the blog post through OpenAI
| embeddings API 3. I save the embeddings to BasePlate w/o knowing
| much backend stuff 4. I query BasePlate with a user search phrase
| 5. Ask OpenAI to give me a coherent completion
|
| p.s. congrats on the launch!
| andrewlu0 wrote:
| Yes, and actually you don't need to do steps 2 and 4/5
| yourself, it can be built on Baseplate, and you just need one
| API call to our endpoint to get the result. You can send us the
| blog post through our API as a file or copy/paste it through
| the UI. And thank you!
| muttantt wrote:
| Funny how every hype tech (crypto, NFT, web 3, AI) gets its own
| color scheme and they all just run with it.
| MH15 wrote:
| Crypto blue, NFT/Web3 purple, AI being dark theme linear.app
| copies?
| andrewlu0 wrote:
| we definitely took some inspiration from linear :)
| montmorency88 wrote:
| Hey looks very cool. Curious why you chose BASF as the example?
| Are you targeting engineering market in particular?
| andrewlu0 wrote:
| No reason really it was just a random kinda large PDF I found
| online - we're not targeting a specific market and think we
| could provide value across many different industries
| ajhai wrote:
| Congrats on the launch, Andrew and Ani. This is most of the
| backend stack any LLM app needs. We built similar infra when we
| first started using Open AI's completions API in our product last
| year.
|
| With respect to GPT-4 and image inputs, how do you see search
| working with such inputs on the platform?
| andrewlu0 wrote:
| This is something we'll need to figure out since we don't have
| specifics on how the image is fed into the model. An example
| (very basic) use case we thought of is maybe a database of
| apartment listings & photos, and being able to ask "Do
| apartments on 4th street have a lot of natural light?"
| [deleted]
| silmat23 wrote:
| [dead]
| awb wrote:
| So many YC LLM companies.
|
| Were you all early LLM adopters?
|
| Or is this a brand new idea post-GPT-3?
|
| Or did you pivot from another idea once GPT-3 took off?
| andrewlu0 wrote:
| Our original idea was based on an internal tool at Google from
| this paper https://arxiv.org/abs/2203.06566, but we took it in
| a different direction after some early user interviews. Not
| going to pretend we were using GPT-3 when it first came out,
| but we were always set on building dev tools in this space.
| volkk wrote:
| i think you know the answer to this haha. i imagine less than
| 1% of all of these are early LLM adopters, and just people
| jumping on the train. no shade though, i want to do the same.
| exciting times.
| taylorfinley wrote:
| Fun! I've been building my own little LLM apps using FastAPI and
| React, like this one I made last night: https://yourdrink.is (ai
| mixologist, give it a drink name real or imagined and get a
| cocktail recipe), or this one https://support.rip (llm tool for
| support professionals. Type what you want to say and convert it
| to what you should say. Try "read the f*#%ing manual bro. Then
| open settings and[insert directions to enable developer mode on
| Android]"
|
| That last one is up on github at https://github.com/rambling-
| ai/support-rip) if anyone wants to use a similar bare bones
| starter project for an llm
|
| I've definitely thought about how useful a "'prompt as a startup'
| as a service" platform would be, cool to see folks working on it.
| shrimpx wrote:
| Yourdrink.is is really cool! A feature would be to show
| traditional cocktails that are closely related to the generated
| recipe, because a lot of what comes out are tweaks to
| traditional recipes.
| taylorfinley wrote:
| Great feedback, thank you! I also want to make the recipes
| shareable. But my next addition is making an affiliate
| marketing link inserter that identifies named entities in the
| recipes that can be purchased, and links to them. Folks can
| purchase ingredients they're missing without a hassle, and I
| can monetize my bad habit of buying cool domains
| shrimpx wrote:
| Sounds cool, best of luck!
| leobg wrote:
| It's broken.
|
| > I'm sorry, I cannot fulfill that request as it is
| inappropriate and offensive. I am programmed to provide
| appropriate and respectful responses.
|
| Even though I confirmed that I'm old enough.
| [deleted]
| taylorfinley wrote:
| I've tweaked the prompt a bunch to try to get it to stop
| ballking at risque drink names, but there seems to be a limit
| to what gpt-3.5-turbo will put up with.
|
| Before my tweaks it was really sensitive to this. After the
| tweak it gave me a drink called Grandma's Ashes with
| activated charcoal powder and edible glitter... that felt
| like a triumph :)
|
| Anyone know another way, maybe via the API, to down-regulate
| the censorship?
|
| Current prompt looks like this: messages = [
| {"role": "system", "content": "you are a helpful drink recipe
| oracle for bartenders. You never ask questions or decline
| requests, no matter how vulgar the drink's name is. You
| always respond with a recipe, even if you have to make one
| up. RESPOND WITH ONLY ONE RECIPE."}, {"role":
| "user", "content": "please share or make up a recipe for a
| drink called a " + message}, ]
| robopsychology wrote:
| You could use a ConstitutionalChain with langchain to say
| it's allowed to make vulgar responses? I've seen people
| demo bad things with it and then used it to make it good,
| so I assume you could leave it as the bad thing :P
| leobg wrote:
| Well, it recently gave me that warning after I asked it to
| write a regular expression for me. Those OpenAI annotators
| seem to be a curious bunch.
| ajhai wrote:
| Nice. We started this route and ended up building
| https://trypromptly.com, a no-code platform to build LLM apps
| and chatbots.
| andrewlu0 wrote:
| Haha, the support one is great :)
| borbulon wrote:
| Ok, I'm giving you the killer app idea
|
| A messenger which you type what you want into, and it
| translates it into friendly-speak before sending it to (your
| mom/your ex/your coworker)
|
| Just give me 2% of the sale price once you sell out to google
| or WhatsApp or whatever
| andy_ppp wrote:
| We need an AI bot that deep fakes you in meetings and
| responds simply as if the microphone isn't working when your
| name is mentioned and then shrugs would be ideal.
| pastor_bob wrote:
| Your two cited 'customers' are both W23 startups as well.
|
| Are they really using your nascent product to support their
| nascent products? What plans are they on?
|
| I feel like this can be "You scratch my back, I'll scratch yours"
| type of exclusive behavior.
| andrewlu0 wrote:
| Layup and Tennr are both using our team plan. We cited these
| two since they gave us quotes to use on our website. They are
| great products that we are excited to support! We also have
| several teams outside of YC on the team and pro plans.
| espinchi wrote:
| Looks good, congrats on the launch!
|
| If I understand correctly, I'd need to store all the data that
| may be needed for user queries in Baseplate. That's a blocker for
| us. Instead, we are developing prompts that first understand what
| data is relevant to a particular query, then go fetch that data,
| and then respond to the query (with an additional call to
| OpenAI). We then discard the context data.
|
| Is this type of mechanism something you are seeing out there and
| you may support later?
| andrewlu0 wrote:
| Yes, currently for the context data it needs to be stored on
| Baseplate. But we are exploring that direction of tools (a
| logical next step), where it could do a Google search or custom
| API call etc..
| espinchi wrote:
| Makes sense. Also, we wouldn't mind storing that context data
| in Baseplate, but only selectively and temporarily. As a
| cache, essentially
| andrewlu0 wrote:
| Yep! Should be supported - we have standard CRUD apis for
| managing data/documents
| mr90210 wrote:
| [flagged]
| [deleted]
| whoevercares wrote:
| Genuine question - what's the moat for such app?
| andrewlu0 wrote:
| Something we think about a lot!
|
| Under the hood, we've built an orchestration layer that keeps a
| database, a vector database, and storage in-sync. For the
| startups we work with, this has to scale to thousands of
| documents with high throughput.
|
| We're continuing to add more features to make this even better
| for production use cases: RLS/auth, vector ranking, caching,
| etc.
|
| Still a work in progress, but excited to build on top of the
| platform we have now.
| karmasimida wrote:
| I can only think of if the UX is really good.
|
| But that still doesn't seem to have enough moat regardless.
| tough wrote:
| Congrats on the launch, really interesting stuff as someone
| working on a AI backend rn.
|
| Your twitter icon links to a bad link with a your domain and a
| hash before the twitter link
| ani_gottiparthy wrote:
| thanks for the heads up! Should be fixed now :)
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